Journal
AUTOMATICA
Volume 133, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.automatica.2021.109853
Keywords
-
Ask authors/readers for more resources
This article extends the concepts of probabilistic ultimate bounds (PUB) and probabilistic invariant sets (PIS) to nonlinear continuous-time systems, providing tools for their characterization and control design. Two design strategies based on Lyapunov and stochastic feedback linearization are proposed to find a nonlinear control law ensuring probabilistic ultimate boundedness of the closed loop system to a desired region.
This article extends the notions of probabilistic ultimate bounds (PUB) and probabilistic invariant sets (PIS) to nonlinear continuous-time systems providing tools for their characterization and for the usage of these concepts in control design. Two design strategies are proposed that allow finding a nonlinear control law which ensures that the closed loop system is probabilistically ultimate bounded to a desired region. These strategies are based on Lyapunov and stochastic feedback linearization, respectively. (C) 2021 Published by Elsevier Ltd.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available